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This study examines the pitch profiles of French learners of German and German learners of French, both in their native language (L1), and in their respective foreign language (L2). Results of the analysis of 84 speakers suggest that for short read sentences, French and German speakers do not show pitch range differences in their native production. Furthermore, analyses of mean f0 and pitch range indicate that range is not necessarily reduced in L2 productions. These results are different from results reported in prior research. Possible reasons for these differences are discussed.
Opinion Holder and Target Extraction for Verb-based Opinion Predicates – The Problem is Not Solved
(2015)
We offer a critical review of the current state of opinion role extraction involving opinion verbs. We argue that neither the currently available lexical resources nor the manually annotated text corpora are sufficient to appropriately study this task. We introduce a new corpus focusing on opinion roles of opinion verbs from the Subjectivity Lexicon and show potential benefits of this corpus. We also demonstrate that state-of-the-art classifiers perform rather poorly on this new dataset compared to the standard dataset for the task showing that there still remains significant research to be done.
We present an approach for opinion role induction for verbal predicates. Our model rests on the assumption that opinion verbs can be divided into three different types where each type is associated with a characteristic mapping between semantic roles and opinion holders and targets. In several experiments, we demonstrate the relevance of those three categories for the task. We show that verbs can easily be categorized with semi-supervised graphbased clustering and some appropriate similarity metric. The seeds are obtained through linguistic diagnostics. We evaluate our approach against a new manually-compiled opinion role lexicon and perform in-context classification.
This article reports on the on-going CoRoLa project, aiming at creating a reference corpus of contemporary Romanian (from 1945 onwards), opened for online free exploitation by researchers in linguistics and language processing, teachers of Romanian, students. We invest serious efforts in persuading large publishing houses and other owners of IPR on relevant language data to join us and contribute the project with selections of their text and speech repositories. The CoRoLa project is coordinated by two Computer Science institutes of the Romanian Academy, but enjoys cooperation of and consulting from professional linguists from other institutes of the Romanian Academy. We foresee a written component of the corpus of more than 500 million word forms, and a speech component of about 300 hours of recordings. The entire collection of texts (covering all functional styles of the language) will be pre-processed and annotated at several levels, and also documented with standardized metadata. The pre-processing includes cleaning the data and harmonising the diacritics, sentence splitting and tokenization. Annotation will include morpho-lexical tagging and lemmatization in the first stage, followed by syntactic, semantic and discourse annotation in a later stage.
To optimize the sharing and reuse of existing data, many funding organizations now require researchers to specify a management plan for research data. In such a plan, researchers are supposed to describe the entire life cycle of the research data they are going to produce, from data creation to formatting, interpretation, documentation, short-term storage, long-term archiving and data re-use. To support researchers with this task, we built DMPTY, a wizard that guides researchers through the essential aspects of managing data, elicits information from them, and finally, generates a document that can be further edited and linked to the original research proposal.
In a project called "A Library of a Billion Words" we needed an implementation of the CTS protocol that is capable of handling a text collection containing at least 1 billion words. Because the existing solutions did not work for this scale or were still in development I started an implementation of the CTS protocol using methods that MySQL provides. Last year we published a paper that introduced a prototype with the core functionalities without being compliant with the specifications of CTS (Tiepmar et al., 2013). The purpose of this paper is to describe and evaluate the MySQL based implementation now that it is fulfilling the specifications version 5.0 rc.1 and mark it as finished and ready to use. Further information, online instances of CTS for all described datasets and binaries can be accessed via the projects website.
We present a quantitative approach to disambiguating flat morphological analyses and producing more deeply structured analyses. Based on existing morphological segmentations, possible combinations of resulting word trees for the next level are filtered first by criteria of linguistic plausibility and then by weighting procedures based on the geometric mean. The frequencies for weighting are derived from three different sources (counts of morphs in a lexicon, counts of largest constituents in a lexicon, counts of token frequencies in a corpus) and can be used either to find the best analysis on the level of morphs or on the next higher constituent level. The evaluation shows that for this task corpus-based frequency counts are slightly superior to counts of lexical data.
In this paper, I present the COW14 tool chain, which comprises a web corpus creation tool called texrex, wrappers for existing linguistic annotation tools as well as an online query software called Colibri2. By detailed descriptions of the implementation and systematic evaluations of the performance of the software on different types of systems, I show that the COW14 architecture is capable of handling the creation of corpora of up to at least 100 billion tokens. I also introduce our running demo system which currently serves corpora of up to roughly 20 billion tokens in Dutch, English, French, German, Spanish, and Swedish
Usenet is a large online resource containing user-generated messages (news articles) organised in discussion groups (newsgroups) which deal with a wide variety of different topics. We describe the download, conversion, and annotation of a comprehensive German news corpus for integration in DeReKo, the German Reference Corpus hosted at the Institut für Deutsche Sprache in Mannheim.
In recent years, theoretical and computational linguistics has paid much attention to linguistic items that form scales. In NLP, much research has focused on ordering adjectives by intensity (tiny < small). Here, we address the task of automatically ordering English adverbs by their intensifying or diminishing effect on adjectives (e.g. extremely small < very small). We experiment with 4 different methods: 1) using the association strength between adverbs and adjectives; 2) exploiting scalar patterns (such as not only X but Y); 3) using the metadata of product reviews; 4) clustering. The method that performs best is based on the use of metadata and ranks adverbs by their scaling factor relative to unmodified adjectives.